Chronic evaluation of a clinical system for deep brain stimulation and recording of neural network activity

Functional network dynamics between the anterior thalamus and the cortex in deep brain stimulation for epilepsy

Owing to its unique connectivity profile with cortical brain regions, and its suggested role in the subcortical propagation of seizures, the anterior nucleus of the thalamus (ANT) has been proposed as a key deep brain stimulation (DBS) target in drug-resistant epilepsy. However, the spatio-temporal interaction dynamics of this brain structure, and the functional mechanisms underlying ANT DBS in epilepsy remain unknown. Here, we study how the ANT interacts with the neocortex in vivo in humans and provide a detailed neurofunctional characterization of mechanisms underlying the effectiveness of ANT DBS, aiming at defining intraoperative neural biomarkers of responsiveness to therapy, assessed at 6 months post-implantation as the reduction in seizure frequency. A cohort of 15 patients with drug-resistant epilepsy (n = 6 males, age = 41.6 ± 13.79 years) underwent bilateral ANT DBS implantation. Using intraoperative cortical and ANT simultaneous electrophysiological recordings, we found that the ANT is characterized by high amplitude θ (4-8 Hz) oscillations, mostly in its superior part. The strongest functional connectivity between the ANT and the scalp EEG was also found in the θ band in ipsilateral centro-frontal regions. Upon intraoperative stimulation in the ANT, we found a decrease in higher EEG frequencies (20-70 Hz) and a generalized increase in scalp-to-scalp connectivity. Crucially, we observed that responders to ANT DBS treatment were characterized by higher EEG θ oscillations, higher θ power in the ANT, and stronger ANT-to-scalp θ connectivity, highlighting the crucial role of θ oscillations in the dynamical network characterization of these structures. Our study provides a comprehensive characterization of the interaction dynamic between the ANT and the cortex, delivering crucial information to optimize and predict clinical DBS response in patients with drug-resistant epilepsy.

Landscape and future directions of machine learning applications in closed-loop brain stimulation

Brain stimulation (BStim) encompasses multiple modalities (e.g., deep brain stimulation, responsive neurostimulation) that utilize electrodes implanted in deep brain structures to treat neurological disorders. Currently, BStim is primarily used to treat movement disorders such as Parkinson's, though indications are expanding to include neuropsychiatric disorders like depression and schizophrenia. Traditional BStim systems are "open-loop" and deliver constant electrical stimulation based on manually-determined parameters. Advancements in BStim have enabled development of "closed-loop" systems that analyze neural biomarkers (e.g., local field potentials in the sub-thalamic nucleus) and adjust electrical modulation in a dynamic, patient-specific, and energy efficient manner. These closed-loop systems enable real-time, context-specific stimulation adjustment to reduce symptom burden. Machine learning (ML) has emerged as a vital component in designing these closed-loop systems as ML models can predict / identify presence of disease symptoms based on neural activity and adaptively learn to modulate stimulation. We queried the US National Library of Medicine PubMed database to understand the role of ML in developing closed-loop BStim systems to treat epilepsy, movement disorders, and neuropsychiatric disorders. Both neural and non-neural network ML algorithms have successfully been leveraged to create closed-loop systems that perform comparably to open-loop systems. For disorders in which the underlying neural pathophysiology is relatively well understood (e.g., Parkinson's, essential tremor), most work has involved refining ML models that can classify neural signals as aberrant or normal. The same is seen for epilepsy, where most current research has focused on identifying optimal ML model design and integrating closed-loop systems into existing devices. For neuropsychiatric disorders, where the underlying pathologic neural circuitry is still being investigated, research is focused on identifying biomarkers (e.g., local field potentials from brain nuclei) that ML models can use to identify onset of symptoms and stratify severity of disease.

Deep brain stimulation of the anterior nuclei of the thalamus can alleviate seizure severity and induce hippocampal GABAergic neuronal changes in a pilocarpine-induced epileptic mouse brain

Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) has been widely used as an effective treatment for refractory temporal lobe epilepsy. Despite its promising clinical outcome, the exact mechanism of how ANT-DBS alleviates seizure severity has not been fully understood, especially at the cellular level. To assess effects of DBS, the present study examined electroencephalography (EEG) signals and locomotor behavior changes and conducted immunohistochemical analyses to examine changes in neuronal activity, number of neurons, and neurogenesis of inhibitory neurons in different hippocampal subregions. ANT-DBS alleviated seizure activity, abnormal locomotor behaviors, reduced theta-band, increased gamma-band EEG power in the interictal state, and increased the number of neurons in the dentate gyrus (DG). The number of parvalbumin- and somatostatin-expressing inhibitory neurons was recovered to the level in DG and CA1 of naïve mice. Notably, BrdU-positive inhibitory neurons were increased. In conclusion, ANT-DBS not only could reduce the number of seizures, but also could induce neuronal changes in the hippocampus, which is a key region involved in chronic epileptogenesis. Importantly, our results suggest that ANT-DBS may lead to hippocampal subregion-specific cellular recovery of GABAergic inhibitory neurons.

Long Term Performance of a Bi-Directional Neural Interface for Deep Brain Stimulation and Recording

Background: In prior reports, we described the design and initial performance of a fully implantable, bi-directional neural interface system for use in deep brain and other neurostimulation applications. Here we provide an update on the chronic, long-term neural sensing performance of the system using traditional 4-contact leads and extend those results to include directional 8-contact leads.

Methods: Seven ovine subjects were implanted with deep brain stimulation (DBS) leads at different nodes within the Circuit of Papez: four with unilateral leads in the anterior nucleus of the thalamus and hippocampus; two with bilateral fornix leads, and one with bilateral hippocampal leads. The leads were connected to either an Activa PC+S^® (Medtronic) or Percept PC^°ledR (Medtronic) deep brain stimulation and recording device. Spontaneous local field potentials (LFPs), evoked potentials (EPs), LFP response to stimulation, and electrode impedances were monitored chronically for periods of up to five years in these subjects.

Results: The morphology, amplitude, and latencies of chronic hippocampal EPs evoked by thalamic stimulation remained stable over the duration of the study. Similarly, LFPs showed consistent spectral peaks with expected variation in absolute magnitude dependent upon behavioral state and other factors, but no systematic degradation of signal quality over time. Electrode impedances remained within expected ranges with little variation following an initial stabilization period. Coupled neural activity between the two nodes within the Papez circuit could be observed in synchronized recordings up to 5 years post-implant. The magnitude of passive LFP power recorded from directional electrode segments was indicative of the contacts that produced the greatest stimulation-induced changes in LFP power within the Papez network.

Conclusion: The implanted device performed as designed, providing the ability to chronically stimulate and record neural activity within this network for up to 5 years of follow-up.

The Translational Benefits of Sheep as Large Animal Models of Human Neurological Disorders

The past two decades have seen a considerable rise in the use of sheep to model human neurological disorders. While each animal model has its merits, sheep have many advantages over small animal models when it comes to studies on the brain. In particular, sheep have brains more comparable in size and structure to the human brain. They also have much longer life spans and are docile animals, making them useful for a wide range of in vivo studies. Sheep are amenable to regular blood and cerebrospinal fluid sampling which aids in biomarker discovery and monitoring of treatment efficacy. Several neurological diseases have been found to occur naturally in sheep, however sheep can also be genetically engineered or experimentally manipulated to recapitulate disease or injury. Many of these types of sheep models are currently being used for pre-clinical therapeutic trials, particularly gene therapy, with studies from several models culminating in potential treatments moving into clinical trials. This review will provide an overview of the benefits of using sheep to model neurological conditions, and highlight naturally occurring and experimentally induced sheep models that have demonstrated translational validity.

Cause of Subharmonics in Local Field Potentials Recorded by Sensing-Enabled Neurostimulator

Sensing-enabled neurostimulators have become an essential technology for recording local field potentials (LFPs) during neurostimulation. However, subharmonics from indeterminate sources make interpreting LFP recordings a challenge. In this study, we investigated the characteristics and the cause of the subharmonics recorded by sensing-enabled neurostimulators. We found that the amplitudes and frequencies of the subharmonics in clinical LFPs varied with stimulation parameters. Using simulated solutions, we demonstrated that these subharmonics were device-generated noise. The cause of the subharmonics was the ripples in the stimulation pulses residual in the final LFP recordings. Our results provided a method to discriminate the subharmonic artifacts and suggested that interpretation of the subharmonics at a fractional frequency of stimulations in LFP recordings should be performed carefully.Clinical Relevance- This study reveals the cause of subharmonics in LFP recordings for clinical neuroscience research.

Acute Brain Activation Patterns of High- Versus Low-Frequency Stimulation of the Anterior Nucleus of the Thalamus During Deep Brain Stimulation for Epilepsy

BACKGROUND

Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is an increasingly utilized treatment of drug-resistant epilepsy. To date, the effect of high-frequency stimulation (HFS) vs low-frequency stimulation (LFS) in ANT DBS is poorly understood.

OBJECTIVE

To assess differences in the acute effect of LFS vs HFS in ANT DBS utilizing blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI).

METHODS

In this prospective study of 5 patients with ANT DBS for epilepsy, BOLD activation and deactivation were modeled for 145-Hz and 30-Hz ANT stimulation using an fMRI block design. Data were analyzed with a general linear model and combined via 2-stage mixed-effects analysis. Z-score difference maps were nonparametrically thresholded using cluster threshold of z > 3.1 and a (corrected) cluster significance threshold of P = .05.

RESULTS

HFS produced significantly greater activation within multiple regions, in particular the limbic and default mode network (DMN). LFS produced minimal activation and failed to produce significant activation within these same networks. HFS produced widespread cortical and subcortical deactivation sparing most of the limbic and DMN regions. Meanwhile, LFS produced deactivation in most DMN and limbic structures.

CONCLUSION

Our results show that HFS and LFS produce substantial variability in both local and downstream network effects. In particular, largely opposing effects were identified within the limbic network and DMN. These findings may serve as a mechanistic basis for understanding the potential of HFS vs LFS in various epilepsy syndromes.

The SANTÉ study at 10 years of follow-up: Effectiveness, safety, and sudden unexpected death in epilepsy

OBJECTIVE

We evaluated the efficacy and safety of deep brain anterior thalamus stimulation after 7 and 10 years, and report the incidence of sudden unexpected death in epilepsy (SUDEP) and overall mortality in adults in the Stimulation of the Anterior Nucleus of the Thalamus for Epilepsy (SANTÉ) study.

METHODS

After the 3-month blinded and 9-month unblinded phases, subjects continued to be assessed during long-term follow-up (LTFU) and later a continued therapy access phase (CAP), to further characterize adverse events and the incidence of SUDEP. Stimulus parameter and medication changes were allowed.

RESULTS

One hundred ten implanted subjects accumulated a total of 938 device-years of experience (69 subjects during the LTFU phase and 61 subjects in the CAP phase). Prior to study closure, 57 active subjects continued therapy at 14 study centers, with follow-up of at least 10 (maximum 14) years. At 7 years, median seizure frequency percent reduction from baseline was 75% (p < .001), with no outcome differences related to prior vagus nerve stimulation or resective surgery. The most severe seizure type, focal to bilateral tonic-clonic, was reduced by 71%. Adding new antiseizure medications did not impact the pattern of seizure reduction over time. There were no unanticipated serious adverse events in the study. The definite-plus-probable SUDEP rate, based on SANTÉ study experience (two deaths in 938 years) and previous pilot studies (0 deaths in 76 years), indicated a rate of 2.0 deaths for 1000 person-years. Overall mortality was 6.9 deaths per 1000 person-years.

SIGNIFICANCE

The long-term efficacy and safety profiles of the deep brain stimulation (DBS) system for epilepsy are favorable and demonstrate stable outcomes. Improvement in frequency of the most severe seizure type may reduce SUDEP risk. The SUDEP rate with DBS (2.0) is comparable to other neuromodulation treatments (i.e., vagus nerve stimulation, responsive neurostimulation) for drug-resistant focal epilepsy.

Blood oxygen level dependent fMRI and perfusion MRI in the sheep brain

The ovine model could be an effective translational model but remains underexplored. Here, Blood Oxygen Level dependent functional MRI during visual stimulation and resting-state perfusion MRI were explored. We aimed at investigating the impact of isoflurane anesthesia during visual stimulation and evaluate resting cerebral blood flow and cerebral blood volume parameters in the lamb and adult sheep brain. BOLD fMRI and perfusion MRI after a bolus of DOTAREM were conducted in 4 lambs and 6 adult ewes at 3 T. A visual stimulation paradigm was delivered during fMRI at increasing isoflurane doses (1-3%). Robust but weak BOLD responses (0.21 ± 0.08%) were found in the lateral geniculate nucleus (LGN) up to 3% isoflurane anaesthesia. No significant differences were found beween BOLD responses in the range 1 to 3% ISO (p > 0.05). However, LGN cluster size decreased and functional localization became less reliable at high ISO doses (2.5-3% ISO). BOLD responses were weaker in adult sheep than in lambs (4.6 ± 1.5 versus 13.6 ± 8.5; p = 0.08). Relative cerebral blood volumes (rCBV) and relative cerebral blood flows (rCBF) were significantly higher (p < 0.0001) in lambs than in adult sheep for both gray and white matter. The impact of volatile anesthesia was explored for the first time on BOLD responses demonstrating increased reliability of functional localization of brain activity at low doses. Perfusion MRI was conducted for the first time in both lambs and adult ewes. Assessment of baseline cerebrovascular values are of interest for future studies of brain diseases allowing an improved interpretation of BOLD responses.

Intelligent automated drug administration and therapy: future of healthcare

In the twenty-first century, the collaboration of control engineering and the healthcare sector has matured to some extent; however, the future will have promising opportunities, vast applications, and some challenges. Due to advancements in processing speed, the closed-loop administration of drugs has gained popularity for critically ill patients in intensive care units and routine life such as personalized drug delivery or implantable therapeutic devices. For developing a closed-loop drug delivery system, the control system works with a group of technologies like sensors, micromachining, wireless technologies, and pharmaceuticals. Recently, the integration of artificial intelligence techniques such as fuzzy logic, neural network, and reinforcement learning with the closed-loop drug delivery systems has brought their applications closer to fully intelligent automatic healthcare systems. This review's main objectives are to discuss the current developments, possibilities, and future visions in closed-loop drug delivery systems, for providing treatment to patients suffering from chronic diseases. It summarizes the present insight of closed-loop drug delivery/therapy for diabetes, gastrointestinal tract disease, cancer, anesthesia administration, cardiac ailments, and neurological disorders, from a perspective to show the research in the area of control theory.

Desynchronization of temporal lobe theta-band activity during effective anterior thalamus deep brain stimulation in epilepsy

BACKGROUND

Bilateral cyclic high frequency deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) reduces the seizure count in a subset of patients with epilepsy. Detecting stimulation-induced alterations of pathological brain networks may help to unravel the underlying physiological mechanisms related to effective stimulation delivery and optimize target engagement.

METHODS

We acquired 64-channel electroencephalography during ten ANT-DBS cycles (145 ​Hz, 90 ​μs, 3-5 ​V) of 1-min ON followed by 5-min OFF stimulation to detect changes in cortical activity related to seizure reduction. The study included 14 subjects (three responders, four non-responders, and seven healthy controls). Mixed-model ANOVA tests were used to compare differences in cortical activity between subgroups both ON and OFF stimulation, while investigating frequency-specific effects for the seizure onset zones.

RESULTS

ANT-DBS had a widespread desynchronization effect on cortical theta and alpha band activity in responders, but not in non-responders. Time domain analysis showed that the stimulation induced reduction in theta-band activity was temporally linked to the stimulation period. Moreover, stimulation induced theta-band desynchronization in the temporal lobe channels correlated significantly with the therapeutic response. Responders to ANT-DBS and healthy-controls had an overall lower level of theta-band activity compared to non-responders.

CONCLUSION

This study demonstrated that temporal lobe channel theta-band desynchronization may be a predictive physiological hallmark of therapeutic response to ANT-DBS and may be used to improve the functional precision of this intervention by verifying implantation sites, calibrating stimulation contacts, and possibly identifying treatment responders prior to implantation.

The Emerging Role of Biomarkers in Adaptive Modulation of Clinical Brain Stimulation

Therapeutic brain stimulation has proven efficacious for treatment of nervous system diseases, exerting widespread influence via disease-specific neural networks. Activation or suppression of neural networks could theoretically be assessed by either clinical symptom modification (ie, tremor, rigidity, seizures) or development of specific biomarkers linked to treatment of symptomatic disease states. For example, biomarkers indicative of disease state could aid improved intraoperative localization of electrode position, optimize device efficacy or efficiency through dynamic control, and eventually serve to guide automatic adjustment of stimulation settings. Biomarkers to control either extracranial or intracranial stimulation span from continuous physiological brain activity, intermittent pathological activity, and triggered local phenomena or potentials, to wearable devices, blood flow, biochemical or cardiac signals, temperature perturbations, optical or magnetic resonance imaging changes, or optogenetic signals. The goal of this review is to update new approaches to implement control of stimulation through relevant biomarkers. Critical questions include whether adaptive systems adjusted through biomarkers can optimize efficiency and eventually efficacy, serve as inputs for stimulation adjustment, and consequently broaden our fundamental understanding of abnormal neural networks in pathologic states. Neurosurgeons are at the forefront of translating and developing biomarkers embedded within improved brain stimulation systems. Thus, criteria for developing and validating biomarkers for clinical use are important for the adaptation of device approaches into clinical practice.

High-frequency stimulation of anterior nucleus of thalamus desynchronizes epileptic network in humans

Epilepsy has been classically seen as a brain disorder resulting from abnormally enhanced neuronal excitability and synchronization. Although it has been described since antiquity, there are still significant challenges achieving the therapeutic goal of seizure freedom. Deep brain stimulation of the anterior nucleus of the thalamus has emerged as a promising therapy for focal drug-resistant epilepsy; the basic mechanism of action, however, remains unclear. Here, we show that desynchronization is a potential mechanism of deep brain stimulation of the anterior nucleus of the thalamus by studying local field potentials recordings from the cortex during high-frequency stimulation (130 Hz) of the anterior nucleus of the thalamus in nine patients with drug-resistant focal epilepsy. We demonstrate that high-frequency stimulation applied to the anterior nucleus of the thalamus desynchronizes ipsilateral hippocampal background electrical activity over a broad frequency range, and reduces pathological epileptic discharges including interictal spikes and high-frequency oscillations. Furthermore, high-frequency stimulation of the anterior nucleus of the thalamus is capable of decoupling large-scale neural activity involving the hippocampus and distributed cortical areas. We found that stimulation frequencies ranging from 15 to 45 Hz were associated with synchronization of hippocampal local field potentials, whereas higher frequencies (>45 Hz) promoted desynchronization of ipsilateral hippocampal activity. Moreover, reciprocal effective connectivity between the anterior nucleus of the thalamus and the hippocampus was demonstrated by hippocampal-thalamic evoked potentials and thalamic-hippocampal evoked potentials. In summary, high-frequency stimulation of the anterior nucleus of the thalamus is shown to desynchronize focal and large-scale epileptic networks, and here is proposed as the mechanism for reducing seizure generation and propagation. Our data also demonstrate position-specific correlation between deep brain stimulation applied to the anterior nucleus of the thalamus and patients with temporal lobe epilepsy and seizure onset zone within the Papaz circuit or limbic system. Our observation may prove useful for guiding electrode implantation to increase clinical efficacy.

Applying a Sensing-Enabled System for Ensuring Safe Anterior Cingulate Deep Brain Stimulation for Pain

Deep brain stimulation (DBS) of the anterior cingulate cortex (ACC) was offered to chronic pain patients who had exhausted medical and surgical options. However, several patients developed recurrent seizures. This work was conducted to assess the effect of ACC stimulation on the brain activity and to guide safe DBS programming. A sensing-enabled neurostimulator (Activa PC + S) allowing wireless recording through the stimulating electrodes was chronically implanted in three patients. Stimulation patterns with different amplitude levels and variable ramping rates were tested to investigate whether these patterns could provide pain relief without triggering after-discharges (ADs) within local field potentials (LFPs) recorded in the ACC. In the absence of ramping, AD activity was detected following stimulation at amplitude levels below those used in chronic therapy. Adjustment of stimulus cycling patterns, by slowly ramping on/off (8-s ramp duration), was able to prevent ADs at higher amplitude levels while maintaining effective pain relief. The absence of AD activity confirmed from the implant was correlated with the absence of clinical seizures. We propose that AD activity in the ACC could be a biomarker for the likelihood of seizures in these patients, and the application of sensing-enabled techniques has the potential to advance safer brain stimulation therapies, especially in novel targets.

A Chronically Implantable Neural Coprocessor for Investigating the Treatment of Neurological Disorders

Developing new tools to better understand disorders of the nervous system, with a goal to more effectively treat them, is an active area of bioelectronic medicine research. Future tools must be flexible and configurable, given the evolving understanding of both neuromodulation mechanisms and how to configure a system for optimal clinical outcomes. We describe a system, the Summit RC+S "neural coprocessor," that attempts to bring the capability and flexibility of a microprocessor to a prosthesis embedded within the nervous system. This paper describes the updated system architecture for the Summit RC+S system, the five custom integrated circuits required for bi-directional neural interfacing, the supporting firmware/software ecosystem, and the verification and validation activities to prepare for human implantation. Emphasis is placed on design changes motivated by experience with the CE-marked Activa PC+S research tool; specifically, enhancement of sense-stim performance for improved bi-directional communication to the nervous system, implementation of rechargeable technology to extend device longevity, and application of MICS-band telemetry for algorithm development and data management. The technology was validated in a chronic treatment paradigm for canines with naturally occurring epilepsy, including free ambulation in the home environment, which represents a typical use case for future human protocols.

A forward-looking review of seizure prediction

PURPOSE OF REVIEW

Seizure prediction has made important advances over the last decade, with the recent demonstration that prospective seizure prediction is possible, though there remain significant obstacles to broader application. In this review, we will describe insights gained from long-term trials, with the aim of identifying research goals for the next decade.

RECENT FINDINGS

Unexpected results from these studies, including strong and highly individual relationships between spikes and seizures, diurnal patterns of seizure activity, and the coexistence of different seizure populations within individual patients exhibiting distinctive dynamics, have caused us to re-evaluate many prior assumptions in seizure prediction studies and suggest alternative strategies that could be employed in the search for algorithms providing greater clinical utility. Advances in analytical approaches, particularly deep-learning techniques, harbour great promise and in combination with less-invasive systems with sufficiently power-efficient computational capacity will bring broader clinical application within reach.

SUMMARY

We conclude the review with an exercise in wishful thinking, which asks what the ideal seizure prediction dataset would look like and how these data should be manipulated to maximize benefits for patients. The motivation for structuring the review in this way is to create a forward-looking, optimistic critique of the existing methodologies.

Intracerebral electroencephalography in targeting anterior thalamic nucleus for deep brain stimulation in refractory epilepsy

BACKGROUND

Results of DBS of ATN in refractory epilepsy depend on accuracy of the electrode's location. We searched for characteristic intraoperative, intracerebral EEG recording pattern from anterior thalamic nuclei (ATNs) as a biological marker for verifying the electrode's position.

METHODS

There were six patients with refractory epilepsy scheduled for deep brain stimulation (DBS) procedure. At surgery, to map the target, we recorded EEG from each lead of DBS electrodes. One patient underwent a 24 hours EEG with continuous recording from both ATNs before internalization of stimulator units.

RESULTS

In all patients we recorded spontaneous bioelectric activity of ATNs. The pattern of the recording from the ATN was similar in all cases. In the one patient where 24-hour recording was done with simultaneous scalp EEG, a complex partial seizure was captured.

CONCLUSION

This is the first report of using DBS electrode for intraoperative EEG recordings from the ATN in patients with refractory epilepsy. Since we managed to find the characteristic pattern of bioelectric activity of ATN, this technique seems to be a promising method for targeting this structure during the operation.

Biomarkers and Stimulation Algorithms for Adaptive Brain Stimulation

The goal of this review is to describe in what ways feedback or adaptive stimulation may be delivered and adjusted based on relevant biomarkers. Specific treatment mechanisms underlying therapeutic brain stimulation remain unclear, in spite of the demonstrated efficacy in a number of nervous system diseases. Brain stimulation appears to exert widespread influence over specific neural networks that are relevant to specific disease entities. In awake patients, activation or suppression of these neural networks can be assessed by either symptom alleviation (i.e., tremor, rigidity, seizures) or physiological criteria, which may be predictive of expected symptomatic treatment. Secondary verification of network activation through specific biomarkers that are linked to symptomatic disease improvement may be useful for several reasons. For example, these biomarkers could aid optimal intraoperative localization, possibly improve efficacy or efficiency (i.e., reduced power needs), and provide long-term adaptive automatic adjustment of stimulation parameters. Possible biomarkers for use in portable or implanted devices span from ongoing physiological brain activity, evoked local field potentials (LFPs), and intermittent pathological activity, to wearable devices, biochemical, blood flow, optical, or magnetic resonance imaging (MRI) changes, temperature changes, or optogenetic signals. First, however, potential biomarkers must be correlated directly with symptom or disease treatment and network activation. Although numerous biomarkers are under consideration for a variety of stimulation indications the feasibility of these approaches has yet to be fully determined. Particularly, there are critical questions whether the use of adaptive systems can improve efficacy over continuous stimulation, facilitate adjustment of stimulation interventions and improve our understanding of the role of abnormal network function in disease mechanisms.

The role of the basal ganglia in the control of seizure

Epilepsy is a network disorder and each type of seizure involves distinct cortical and subcortical network, differently implicated in the control and propagation of the ictal activity. The role of the basal ganglia has been revealed in several cases of focal and generalized seizures. Here, we review the data that show the implication of the basal ganglia in absence, temporal lobe, and neocortical seizures in animal models (rodent, cat, and non-human primate) and in human. Based on these results and the advancement of deep brain stimulation for Parkinson's disease, basal ganglia neuromodulation has been tested with some success that can be equally seen as promising or disappointing. The effect of deep brain stimulation can be considered promising with a 76% in seizure reduction in temporal lobe epilepsy patients, but also disappointing, since only few patients have become seizure free and the antiepileptic effects have been highly variable among patients. This variability could probably be explained by the heterogeneity among the patients included in these clinical studies. To illustrate the importance of specific network identification, electrophysiological activity of the putamen and caudate nucleus has been recorded during penicillin-induced pre-frontal and motor seizures in one monkey. While an increase of the firing rate was found in putamen and caudate nucleus during pre-frontal seizures, only the activity of the putamen cells was increased during motor seizures. These preliminary results demonstrate the implication of the basal ganglia in two types of neocortical seizures and the necessity of studying the network to identify the important nodes implicated in the propagation and control of each type of seizure.

The ovine motor cortex: A review of functional mapping and cytoarchitecture

In recent years, sheep (Ovis aries) have emerged as a useful animal model for neurological research due to their relatively large brain and blood vessel size, their cortical architecture, and their docile temperament. However, the functional anatomy of sheep brain is not as well studied as that of non-human primates, rodents, and felines. For example, while the location of the sheep motor cortex has been known for many years, there have been few studies of the somatotopy of the motor cortex and there were a range of discrepancies across them. The motivation for this review is to provide a definitive resource for studies of the sheep motor cortex. This work critically reviews the literature examining the organization of the motor cortex in sheep, utilizing studies that have applied direct electrical stimulation and histological methods A clearer understanding of the sheep brain will facilitate and progress the use of this species as a scientific animal model for neurological research.

Effects of hippocampal low-frequency stimulation in idiopathic non-human primate epilepsy assessed via a remote-sensing-enabled neurostimulator

Individuals with pharmacoresistant epilepsy remain a large and under-treated patient population. Continued technologic advancements in implantable neurostimulators have spurred considerable research efforts directed towards the development of novel antiepileptic stimulation therapies. However, the lack of adequate preclinical experimental platforms has precluded a detailed understanding of the differential effects of stimulation parameters on neuronal activity within seizure networks. In order to chronically monitor seizures and the effects of stimulation in a freely-behaving non-human primate with idiopathic epilepsy, we employed a novel simultaneous video-intracranial EEG recording platform using a state-of-the-art sensing-enabled, rechargeable clinical neurostimulator with real-time seizure detection and wireless data streaming capabilities. Using this platform, we were able to characterize the electrographic and semiologic features of the focal-onset, secondarily generalizing tonic-clonic seizures stably expressed in this animal. A series of acute experiments exploring low-frequency (2Hz) hippocampal stimulation identified a pulse width (150μs) and current amplitude (4mA) combination which maximally suppressed local hippocampal activity. These optimized stimulation parameters were then delivered to the seizure onset-side hippocampus in a series of chronic experiments. This long-term testing revealed that the suppressive effects of low-frequency hippocampal stimulation 1) diminish when delivered continuously but are maintained when stimulation is cycled on and off, 2) are dependent on circadian rhythms, and 3) do not necessarily confer seizure protective effects.

Closed-loop neuromodulation systems: next-generation treatments for psychiatric illness

Despite deep brain stimulation's positive early results in psychiatric disorders, well-designed clinical trials have yielded inconsistent clinical outcomes. One path to more reliable benefit is closed-loop therapy: stimulation that is automatically adjusted by a device or algorithm in response to changes in the patient's electrical brain activity. These interventions may provide more precise and patient-specific treatments. This article first introduces the available closed-loop neuromodulation platforms, which have shown clinical efficacy in epilepsy and strong early results in movement disorders. It discusses the strengths and limitations of these devices in the context of psychiatric illness. It then describes emerging technologies to address these limitations, including pre-clinical developments such as wireless deep neurostimulation and genetically targeted neuromodulation. Finally, ongoing challenges and limitations for closed-loop psychiatric brain stimulation development, most notably the difficulty of identifying meaningful biomarkers for titration, are discussed. This is considered in the recently-released Research Domain Criteria (RDoC) framework, and how neuromodulation and RDoC are jointly very well suited to address the problem of treatment-resistant illness is described.

Variations in Thalamic Anatomy Affect Targeting in Deep Brain Stimulation for Epilepsy

BACKGROUND

Thalamic size and shape vary significantly across patients - with changes specific to the anterior thalamus occurring with age and in the setting of chronic epilepsy. Such ambiguity raises concerns regarding electrode position and potential implications for seizure outcomes.

METHODS

MRIs from 6 patients from a single center underwent quantitative analysis. In addition to direct measurements from postimplantation MRIs, the CRAnialVault Explorer suite was used to normalize electrode position to a common reference system. Relationships between thalamic dimensions, electrode location, and seizure outcome were analyzed.

RESULTS

Although this study group was too small to sufficiently power statistical analysis, general trends were identified. There was a trend towards smaller thalamic volumes in nonresponders. Electrode locations demonstrated more variation after normalization. There was a trend towards a more lateral, posterior, and inferior electrode position in nonresponders.

CONCLUSIONS

Variations in thalamic shape and volume necessitate direct targeting. Given that changes occur to thalamic anatomy with age and in the setting of epilepsy, improved methods for visualizing and targeting the anterior nucleus are necessary. Pronounced thalamic atrophy may preclude proper electrode placement and serve as a poor prognostic indicator. A greater understanding of thalamic anatomy and connectivity is necessary to optimize deep brain stimulation for epilepsy.

Seizure Prediction: Science Fiction or Soon to Become Reality?

This review highlights recent developments in the field of epileptic seizure prediction. We argue that seizure prediction is possible; however, most previous attempts have used data with an insufficient amount of information to solve the problem. The review discusses four methods for gaining more information above standard clinical electrophysiological recordings. We first discuss developments in obtaining long-term data that enables better characterisation of signal features and trends. Then, we discuss the usage of electrical stimulation to probe neural circuits to obtain robust information regarding excitability. Following this, we present a review of developments in high-resolution micro-electrode technologies that enable neuroimaging across spatial scales. Finally, we present recent results from data-driven model-based analyses, which enable imaging of seizure generating mechanisms from clinical electrophysiological measurements. It is foreseeable that the field of seizure prediction will shift focus to a more probabilistic forecasting approach leading to improvements in the quality of life for the millions of people who suffer uncontrolled seizures. However, a missing piece of the puzzle is devices to acquire long-term high-quality data. When this void is filled, seizure prediction will become a reality.

Anterior nuclear deep brain stimulation guided by concordant hippocampal recording

OBJECT

Anterior nuclear (AN) stimulation has been reported to reduce the frequency of seizures, in some cases dramatically; however, it has not been approved by the US Food and Drug Administration. The anterior nucleus is difficult to target because of its sequestered location, partially surrounded by the ventricle. It has traditionally been targeted by using transventricular or lateral transcortical routes. Here, the authors report a novel approach to targeting the anterior nucleus and neurophysiologically confirming effective stimulation of the target, namely evoked potentials in the hippocampus.

METHODS

Bilateral AN 3389 electrodes were placed in a novel trajectory followed by bilateral hippocampal 3391 electrodes from a posterior trajectory. Each patient was implanted bilaterally with a Medtronic Activa PC+S device under an investigational device exemption approval. Placement was confirmed with CT. AN stimulation-induced hippocampal evoked potentials were measured to functionally confirm placement in the anterior nucleus.

RESULTS

Two patients had implantations by way of a novel AN trajectory with concomitant hippocampal electrodes. There were no lead misplacements. Postoperative stimulation of the anterior nucleus with a PC+S device elicited evoked potentials in the hippocampus. Thus far, both patients have reported a > 50% improvement in seizure frequency.

CONCLUSIONS

Placing AN electrodes posteriorly may provide a safer trajectory than that used for traditionally placed AN electrodes. In addition, with a novel battery that is capable of electroencephalographic recording, evoked potentials can be used to functionally assess the Papez circuit. This treatment paradigm may offer increased AN stimulation efficacy for medically intractable epilepsy by assessing functional placement more effectively and thus far has proven safe.

High Frequency Deep Brain Stimulation and Neural Rhythms in Parkinson's Disease

High frequency (HF) deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease (PD). It effectively treats the cardinal motor signs of PD, including tremor, bradykinesia, and rigidity. The most common neural target is the subthalamic nucleus, located within the basal ganglia, the region most acutely affected by PD pathology. Using chronically-implanted DBS electrodes, researchers have been able to record underlying neural rhythms from several nodes in the PD network as well as perturb it using DBS to measure the ensuing neural and behavioral effects, both acutely and over time. In this review, we provide an overview of the PD neural network, focusing on the pathophysiological signals that have been recorded from PD patients as well as the mechanisms underlying the therapeutic benefits of HF DBS. We then discuss evidence for the relationship between specific neural oscillations and symptoms of PD, including the aberrant relationships potentially underlying functional connectivity in PD as well as the use of different frequencies of stimulation to more specifically target certain symptoms. Finally, we briefly describe several current areas of investigation and how the ability to record neural data in ecologically-valid settings may allow researchers to explore the relationship between brain and behavior in an unprecedented manner, culminating in the future automation of neurostimulation therapy for the treatment of a variety of neuropsychiatric diseases.

Local field potential recordings in a non-human primate model of Parkinsons disease using the Activa PC + S neurostimulator

OBJECTIVE

Using the Medtronic Activa® PC + S system, this study investigated how passive joint manipulation, reaching behavior, and deep brain stimulation (DBS) modulate local field potential (LFP) activity in the subthalamic nucleus (STN) and globus pallidus (GP).

APPROACH

Five non-human primates were implanted unilaterally with one or more DBS leads. LFPs were collected in montage recordings during resting state conditions and during motor tasks that facilitate the expression of parkinsonian motor signs. These recordings were made in the naïve state in one subject, in the parkinsonian state in two subjects, and in both naïve and parkinsonian states in two subjects.

MAIN RESULTS

LFPs measured at rest were consistent over time for a given recording location and parkinsonian state in a given subject; however, LFPs were highly variable between subjects, between and within recording locations, and across parkinsonian states. LFPs in both naïve and parkinsonian states across all recorded nuclei contained a spectral peak in the beta band (10-30 Hz). Moreover, the spectral content of recorded LFPs was modulated by passive and active movement of the subjects' limbs. LFPs recorded during a cued-reaching task displayed task-related beta desynchronization in STN and GP. The bidirectional capabilities of the Activa® PC + S also allowed for recording LFPs while delivering DBS. The therapeutic effect of STN DBS on parkinsonian rigidity outlasted stimulation for 30-60 s, but there was no correlation with beta band power.

SIGNIFICANCE

This study emphasizes (1) the variability in spontaneous LFPs amongst subjects and (2) the value of using the Activa® PC + S system to record neural data in the context of behavioral tasks that allow one to evaluate a subject's symptomatology.

Outcome based definition of the anterior thalamic deep brain stimulation target in refractory epilepsy

BACKGROUND

Deep brain stimulation of the anterior nucleus of the thalamus (ANT) is an emerging therapy for refractory focal epilepsy. However, the most optimal target for stimulation has not been unambiguously described.

OBJECTIVE

In the present study, we investigated the correlation between the stimulation site and outcome in order to define the optimal target for deep brain stimulation in refractory epilepsy.

METHODS

The locations of 62 contacts used in 30 treatment attempts in 15 prospectively followed patients during a 5 year period were assessed. Treatment attempts were classified into responding and non-responding trials using seizure reduction and side effect profile as criteria. The locations of active contacts were calculated with respect to mid-commissural point and visible borders of ANT in 3T MRI (ANT-normalized coordinate system) aiming to minimize the confounding effect of individual variation in the location and size of the ANT.

RESULTS

Contacts in successful treatment trials were located significantly more anterior and superior both in AC-PC and ANT-normalized coordinate systems. Favourable outcome was observed at 3T MRI based location of ANT but not at location predicted by Schaltenbrandt atlas sagittal data. Contacts used in successful trials were at anterior aspect of the ANT complex evidenced by the ANT-normalized coordinate system.

CONCLUSION

The anti-epileptic effect of anterior thalamic DBS may be dependent on stimulation site especially in the anterior to posterior axis. Extensive anatomical variation confounds severely the targeting of ANT. Therefore, direct visualization of the desired target for stimulation is essential for favourable outcome in refractory epilepsy.

Beta oscillations in freely moving Parkinson's subjects are attenuated during deep brain stimulation

BACKGROUND

Investigations into the effect of deep brain stimulation (DBS) on subthalamic (STN) beta (13-30 Hz) oscillations have been performed in the perioperative period with the subject tethered to equipment. Using an embedded sensing neurostimulator, this study investigated whether beta power was similar in different resting postures and during forward walking in freely moving subjects with Parkinson's disease (PD) and whether STN DBS attenuated beta power in a voltage-dependent manner.

METHODS

Subthalamic local field potentials were recorded from the DBS lead, using a sensing neurostimulator (Activa(®) PC+S, Medtronic, Inc., Food and Drug Administration- Investigational Device Exemption (IDE)-, institutional review board-approved) from 15 PD subjects (30 STNs) off medication during lying, sitting, and standing, during forward walking, and during randomized periods of 140 Hz DBS at 0 V, 1 V, and 2.5/3 V. Continuous video, limb angular velocity, and forearm electromyography recordings were synchronized with neural recordings. Data were parsed to avoid any movement or electrical artifact during resting states.

RESULTS

Beta power was similar during lying, sitting, and standing (P = 0.077, n = 28) and during forward walking compared with the averaged resting state (P = 0.466, n = 24), although akinetic rigid PD subjects tended to exhibit decreased beta power when walking. Deep brain stimulation at 3 V and at 1 V attenuated beta power compared with 0 V (P < 0.003, n = 14), and this was voltage dependent (P < 0.001).

CONCLUSIONS

Beta power was conserved during resting and forward walking states and was attenuated in a voltage-dependent manner during 140-Hz DBS. Phenotype may be an important consideration if this is used for closed-loop DBS.

A method for actively tracking excitability of brain networks using a fully implantable monitoring system

This paper introduces a new method for estimating the excitability of brain networks. The motivation for this research was to develop a system that can track pathological changes in excitability, in diseases such as epilepsy. The ability to track excitability may provide a method for anticipating seizures and intervening therapeutically. Four normally healthy canines were implanted with the Medtronic Activia PC+S deep brain stimulation and sensing system. The devices were used to probe the circuit of Papez, with electrical stimulation in the anterior nucleus of the thalamus to measure evoked potentials in the hippocampus. The canines were given three different dosage levels of anti-convulsant medication in an attempt to manipulate the excitability of the network. The results showed changes in the morphology of the evoked potentials, following a circadian profile and reflecting times of drug delivery.

A flexible algorithm framework for closed-loop neuromodulation research systems

Modulation of neural activity through electrical stimulation of tissue is an effective therapy for neurological diseases such as Parkinson's disease and essential tremor. Researchers are exploring improving therapy through adjustment of stimulation parameters based upon sensed data. This requires classifiers to extract features and estimate patient state. It also requires algorithms to appropriately map the state estimation to stimulation parameters. The latter, known as the control policy algorithm, is the focus of this work. Because the optimal control policy algorithms for the nervous system are not fully characterized at this time, we have implemented a generic control policy framework to facilitate exploratory research and rapid prototyping of new neuromodulation strategies.

The Epilepsy Foundation's 4th Biennial Epilepsy Pipeline Update Conference

On June 5 and 6, 2014, the Epilepsy Foundation held its 4th Biennial Epilepsy Pipeline Update Conference, an initiative of the Epilepsy Therapy Project, which showcased the most promising epilepsy innovations from health-care companies and academic laboratories dedicated to pioneering and advancing drugs, biologics, technologies, devices, and diagnostics for epilepsy. Speakers and attendees included emerging biotech and medical technology companies, major pharmaceutical and device companies, as well as investigators and innovators at the cutting-edge of epilepsy. The program included panel discussions on collaboration between small and large companies, how to get products in need of funding to the marketplace, who is currently funding epilepsy and CNS innovation, and how the NIH facilitates early-stage drug development. Finally, the conference featured the third annual "Shark Tank" competition. The presentations are summarized in this paper, which is followed by a compilation of the meeting poster abstracts.

Sensing-enabled hippocampal deep brain stimulation in idiopathic nonhuman primate epilepsy

Epilepsy is a debilitating condition affecting 1% of the population worldwide. Medications fail to control seizures in at least 30% of patients, and deep brain stimulation (DBS) is a promising alternative treatment. A modified clinical DBS hardware platform was recently described (PC+S) allowing long-term recording of electrical brain activity such that effects of DBS on neural networks can be examined. This study reports the first use of this device to characterize idiopathic epilepsy and assess the effects of stimulation in a nonhuman primate (NHP). Clinical DBS electrodes were implanted in the hippocampus of an epileptic NHP bilaterally, and baseline local field potential (LFP) recordings were collected for seizure characterization with the PC+S. Real-time automatic detection of ictal events was demonstrated and validated by concurrent visual observation of seizure behavior. Seizures consisted of large-amplitude 8- to 25-Hz oscillations originating from the right hemisphere and quickly generalizing, with an average occurrence of 0.71 ± 0.15 seizures/day. Various stimulation parameters resulted in suppression of LFP activity or in seizure induction during stimulation under ketamine anesthesia. Chronic stimulation in the awake animal was studied to evaluate how seizure activity was affected by stimulation configurations that suppressed broadband LFPs in acute experiments. This is the first electrophysiological characterization of epilepsy using a next-generation clinical DBS system that offers the ability to record and analyze neural signals from a chronically implanted stimulating electrode. These results will direct further development of this technology and ultimately provide insight into therapeutic mechanisms of DBS for epilepsy.

Neurostimulation for traumatic brain injury

Traumatic brain injury (TBI) remains a significant public health problem and is a leading cause of death and disability in many countries. Durable treatments for neurological function deficits following TBI have been elusive, as there are currently no FDA-approved therapeutic modalities for mitigating the consequences of TBI. Neurostimulation strategies using various forms of electrical stimulation have recently been applied to treat functional deficits in animal models and clinical stroke trials. The results from these studies suggest that neurostimulation may augment improvements in both motor and cognitive deficits after brain injury. Several studies have taken this approach in animal models of TBI, showing both behavioral enhancement and biological evidence of recovery. There have been only a few studies using deep brain stimulation (DBS) in human TBI patients, and future studies are warranted to validate the feasibility of this technique in the clinical treatment of TBI. In this review, the authors summarize insights from studies employing neurostimulation techniques in the setting of brain injury. Moreover, they relate these findings to the future prospect of using DBS to ameliorate motor and cognitive deficits following TBI.

Deep brain stimulation for the treatment of epilepsy: circuits, targets, and trials

Deep brain stimulation (DBS) has proven remarkably safe and effective in the treatment of movement disorders. As a result, it is being increasingly applied to a range of neurologic and psychiatric disorders, including medically refractory epilepsy. This review will examine the use of DBS in epilepsy, including known targets, mechanisms of neuromodulation and seizure control, published clinical evidence, and novel technologies. Cortical and deep neuromodulation for epilepsy has a long experimental history, but only recently have better understanding of epileptogenic networks, precise stereotactic techniques, and rigorous trial design combined to improve the quality of available evidence and make DBS a viable treatment option. Nonetheless, underlying mechanisms, anatomical targets, and stimulation parameters remain areas of active investigation.

Closed-loop neurostimulation: the clinical experience

Neurostimulation is now an established therapy for the treatment of movement disorders, pain, and epilepsy. While most neurostimulation systems available today provide stimulation in an open-loop manner (i.e., therapy is delivered according to preprogrammed settings and is unaffected by changes in the patient's clinical symptoms or in the underlying disease), closed-loop neurostimulation systems, which modulate or adapt therapy in response to physiological changes, may provide more effective and efficient therapy. At present, few such systems exist owing to the complexities of designing and implementing implantable closed-loop systems. This review focuses on the clinical experience of four implantable closed-loop neurostimulation systems: positional-adaptive spinal cord stimulation for treatment of pain, responsive cortical stimulation for treatment of epilepsy, closed-loop vagus nerve stimulation for treatment of epilepsy, and concurrent sensing and stimulation for treatment of Parkinson disease. The history that led to the development of the closed-loop systems, the sensing, detection, and stimulation technology that closes the loop, and the clinical experiences are presented.

Variation in deep brain stimulation electrode impedance over years following electrode implantation

BACKGROUND

Deep brain stimulation (DBS) electrode impedance is a major determinant of current delivery to target tissues, but long-term variation in impedance has received little attention.

OBJECTIVES

To assess the relationship between electrode impedance and time in a large DBS patient population and characterize the relationship between contact activity and impedance.

METHODS

We collected retrospective impedance and programming data from 128 electrodes in 84 patients with Parkinson's disease, essential tremor or dystonia. Effects of time, contact activity, stimulation voltage and other parameters on impedance were assessed. We also examined impedance changes following contact activation and deactivation.

RESULTS

Impedance decreased by 73 Ω/year (p < 0.001), with 72% of contacts following a downward trend. Impedance was on average 163 Ω lower in active contacts (p < 0.001). Contact activation and inactivation were associated with a more (p < 0.001) and less (p = 0.016) rapid decline in impedance, respectively. Higher stimulation voltages were associated with lower impedance values (p < 0.001). Contact number and electrode model were also significant predictors of impedance.

CONCLUSIONS

Impedance decreases gradually in a stimulation-dependent manner. These trends have implications for long-term programming, the development of a closed-loop DBS device and current understanding of the electrode-tissue interface.

Placement of deep brain electrodes in the dog using the Brainsight frameless stereotactic system: a pilot feasibility study

Background

Deep brain stimulation (DBS) together with concurrent EEG recording has shown promise in the treatment of epilepsy. A novel device is capable of combining these 2 functions and may prove valuable in the treatment of epilepsy in dogs. However, stereotactic implantation of electrodes in dogs has not yet been evaluated.

Objective

To evaluate the feasibility and safety of implanting stimulating and recording electrodes in the brain of normal dogs using the Brainsight system and to evaluate the function of a novel DBS and recording device.

Animals

Four male intact Greyhounds, confirmed to be normal by clinical and neurologic examinations and hematology and biochemistry testing.

Methods

MRI imaging of the brain was performed after attachment of fiducial markers. MRI scans were used to calculate trajectories for electrode placement in the thalamus and hippocampus, which was performed via burr hole craniotomy. Postoperative CT scanning was performed to evaluate electrode location and accuracy of placement was calculated. Serial neurologic examinations were performed to evaluate neurologic deficits and EEG recordings obtained to evaluate the effects of stimulation.

Results

Electrodes were successfully placed in 3 of 4 dogs with a mean accuracy of 4.6 ± 1.5 mm. EEG recordings showed evoked potentials in response to stimulation with a circadian variation in time‐to‐maximal amplitude. No neurologic deficits were seen in any dog.

Conclusions and Clinical Importance

Stereotactic placement of electrodes is safe and feasible in the dog. The development of a novel device capable of providing simultaneous neurostimulation and EEG recording potentially represents a major advance in the treatment of epilepsy.